%0 Journal Article
%T AUTOMATIC ANALYSIS OF G BAND OF CULTIVATED WHEAT CHROMOSOME USING NEURAL NETWORK<br>小麦染色体高分辨率G带的神经网络自动分析的研究
%A XIONG Hai-tao
%A HU Kuang-hu
%A SUN Yan
%A LI Shu-yu
%A CAI Nian
%A <br>熊海涛
%A 胡匡祜
%A 孙艳
%A 李淑宇
%A 蔡念
%J 生物物理学报
%D 2000
%I 
%X This paper presents a Double Kohonen Neural Network (DKNN) lased on the Self-Organize Feature Mapping theory to analyge chomosome automatiolly. The DKNN consists of two layers, each of which is a Kohonen network. The first layer maps a 2-d plane to a 2-d feature space to extract the high-resolution bands of chromosome and to compute the parameters of bands. The second layer maps the arrays of high dimension feature parameters to a 2-d plane to pair and classify the chromosomes automatically. The result indicates that this method can extract the feature parameters of G band in the chromosomes of cultivated wheat and then pair them automatically, rapidly and accurately.
%K Self-Organize Feature Mapping
%K Neural Network
%K G band of chromosome in high resolution
%K Auto-analysis of chromoso<br>神经网络
%K G带带纹
%K 染色体
%K 自动分析
%K 小麦
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=90BA3D13E7F3BC869AC96FB3DA594E3FE34FBF7B8BC0E591&jid=E0C9D9BBED813D6674AC13E942EAC86D&aid=3BA146379F198E05&yid=9806D0D4EAA9BED3&vid=7801E6FC5AE9020C&iid=E158A972A605785F&sid=B60458D1AE87BCD1&eid=3EE58D91F4253193&journal_id=1000-6737&journal_name=生物物理学报&referenced_num=0&reference_num=3